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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/9553


    Title: Meditation EEG Interpretation Based on Novel Fuzzy-Merging Strategies and Wavelet Features
    Authors: Kang-Ming Chang;Pei-Chen Lo
    Keywords: Meditation EEG (electroencephalogram) scoring;Wavelet analysis;Fuzzy c-means;clustering (FCM);meditation scenario
    Date: 2005-08
    Issue Date: 2010-05-12 01:12:14 (UTC+0)
    Publisher: Asia University
    Abstract: As the advantages of meditation have been outlined literally, scientific exploration of the meditation phenomena becomes significant. Meditation EEG may provide an access to the mental states beyond normal consciousness. It is the first attempt to score the meditation course by EEG. Wavelet analysis and fuzzy c-means (FCM) are applied in the automatic interpretation algorithm. However, FCM applied straightforward to quantitative feature vectors often results in an over-trifling interpretation. As a consequence, this paper presents novel cluster-managing strategies for achieving an interpretation closer to the result of naked-eye examination. The running gray-scale chart, derived by extracting, clustering, and coding the EEG features, reveals five different meditation scenarios differing from those of the controlled subjects.
    Relation: Journal of Biomedical Engineering-Applications, Basis & Communications 17: 167-175
    Appears in Collections:[光電與通訊學系] 期刊論文

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